| File | What | When |
|---|---|---|
W07_lecture.html
(.qmd source) |
Lecture slides — Parts A, B, C, D | in class |
W07_lab.ipynb
(Colab) |
In-class lab: regularity decides the rate (interpolating r^\alpha), four ways to compute an error, the L-shaped domain, graded meshes, LLM demo | in class (≈ 80 min) |
W07_HW7.ipynb
(Colab) |
HW7 — a rate report: proofs (weak derivatives, Aubin–Nitsche, zero error), predicted vs observed rates on a smooth and two corner problems with uniform and graded meshes, measurement pitfalls, LLM claims checked against your numbers | due before Week 8 |
../dolfinx_0.11_api_reference.md |
DOLFINx 0.11 API reference sheet (§11 parallel-safe norms) — paste it into your LLM | always |
Open a notebook in Colab: click its link on the
course page or below — it opens in Colab; then File → Save a copy in
Drive and work on that copy. (Or upload the .ipynb to
Google Drive → right-click → Open with → Google Colaboratory.)
Run the setup cell first (≈ 3–5 min); re-run it after every runtime
restart.
Where code can run: basix,
ufl, dolfinx are used only inside
%%fenicsx cells. Ordinary cells have NumPy and matplotlib
only.
Before submitting: Runtime → Restart session and
run all, fill in the AI-usage log, download the
.ipynb. An error inside a %%fenicsx cell does
not stop Run all: the traceback is printed and
the next cell runs anyway. Scroll through every output before you
submit. A cell that printed a traceback, and any plot that uses its
results, earns no points.
Week 8 starts with the midterm exam (Weeks 1–7, closed-AI, 90 minutes) — there is no separate quiz on this week’s material.